Pada artikel ini kami mengevaluasi bagaimana implementasi algoritma machine learning k-
Nearest Neighbors (kNN) pada data spektroskopi gamma beresolusi rendah. Penelitian ini …

This research aims at comparing the performance of different machine learning algorithms
used for NaI (TI) gamma-ray detector based radioisotope identification. Six machine learning …

Abstract The K-Nearest Neighbor (K-NN) method is one of the oldest and most popular
Nearest Neighbor-based methods. The researchers developed several methods to improve …

An artificial neural network (ANN) that identifies radionuclides from low-count gamma
spectra of a NaI scintillator is proposed. The ANN was trained and tested using simulated …

K-Nearest Neighbors method is one of methods used for classification which calculate a
value to find out the closest in distance. It is used to group a set of data such as students' …

This article presents a study on the state-of-the-art methods for automated radioactive
material detection and identification, using gamma-ray spectra and modern machine …

Neutron–gamma discrimination plays a fundamental role in the fields of radiation protection
and nuclide identification. The pulse-shape discrimination (PSD) of liquid scintillators has …

FWk-NN is an improvement of k-NN, where FWk-NN gives weight to each data feature
thereby reducing the influence of features that are less relevant to the target. Feature …

Data on graduate students is an important part in determining the quality of a private and
public university. Graduate data is included in important assessments in the accreditation …

Abstract Algoritma k Nearest Neighbor (kNN) merupakan metode untuk melakukan
klasifikasi terhadap objek baru berdasarkan k tetangga terdekatnya. Algoritma kNN memiliki …